journal of medical and bioengineering vol. 4, no. 5

The Cardiovascular and Respiratory Responses to

CO2 under Hyperventilation and Posture Change

in Parkinson’s Patients

Shyan-Lung Lin Department of Information Communication, MingDao University, Changhua, Taiwan

Department of Automatic Control Engineering, Feng Chia University, Taichung, Taiwan

Email: [email protected]; [email protected]

Andy Ying-Chi Liao and Shoou-Jeng Yeh

Cheng Ching Hospital/Department of Neurology, Taichung, Taiwan

Email: [email protected], [email protected]

Abstract—In this paper, study is focused on patients with

autonomic dysfunction, such as Parkinson's disease, and

how the interaction between cerebral autoregulation and

ventilatory control is affected under hyperventilation and

posture changes. Experiments were designed with 13

healthy youth subjects, 10 healthy elder subjects, and 13

subjects with Parkinson's disease (PD) to acquire

cardiovascular and respiratory signals during supine, head-

up tilt (HUT), and hypocapnia. Signal processing is

performed to obtain the end-tidal partial pressure of carbon

dioxide (PETCO2) throughout the hypocapnic range and their

corresponding cardiovascular and respiratory signals,

including mean systolic blood pressure (MSBP), mean

arterial blood pressure (MABP), mean heart rate (MHR),

mean breathing rate (MBR), and mean cerebral blood flow

velocity (MCBFV). Analysis was further achieved to study

the variations in parameters to changes in PETCO2 and to

depict their variation over time. The results of the different

analysis all pointed to suggesting that although Parkinson’s

patients still retain some form of cerebral auto-regulation,

they do not have the range of blood flow regulation that a

healthy subject does and reactivity to CO2 is limited to a

smaller range.

Index Terms—autonomic dysfunction, Parkinson's disease,

hyperventilation, posture changes, cerebral blood flow

I. INTRODUCTION

One of the many health issues that come with old age

is the degradation of the nervous system. When the

nerves degrade, they are no longer able to function at full

capacity and the nerves lose their mass and have defects

in their structure, which leads to a reduced impulse

transmission time [1]. The impairment or malfunction of

the autonomic nervous system is known as dysautonomia

or autonomic dysfunction. Some of the symptoms that

suggest autonomic insufficiency are lightheadedness from

standing up, heat intolerance, loss of bladder and bowel

Manuscript received July 25, 2014; revised October 25, 2014.

control, or erectile dysfunction. As blood pressure rises,

the amount of blood flow in the brain is restricted as to

prevent over-perfusion. The restriction in blood flow is

accomplished by changing blood vessel diameter and

increasing resistance. There are many mechanisms

contributing to the regulation of cerebral blood flow [2],

but this study will largely focus on the chemical influence.

The relationship between middle cerebral artery (MCA)

blood velocity and end-tidal partial pressure of carbon

dioxide (PETCO2) throughout the hypocapnic-hypercapnic

range in humans was examined in an earlier study [3].

The MCA peak blood velocity responses to 14 different

levels of PETCO2 from 22 to 50 Torr were tested and the

result showed that cerebral vasomotor reactivity (CVMR)

were nonlinear with different sensitivities during

hypocapnia and hypercapnia. Further analysis on the non-

linear responses of cerebral blood flow (CBF) to PETCO2

was performed [4]. Because arterial blood pressure (ABP)

also affects CBF, the cerebral vasomotor reactivity index

(CVCi) was utilized instead of to eliminate effects of

ABP and get a more accurate analysis of the response to

PETCO2. The MCA blood flow velocity and mean arterial

blood pressure (MAP) changes to different PETCO2 were

measured and studied in 16 healthy subjects to investigate

the effects of ABP on CBF and its response to CO2 along

with the blood pressure component [5]. Different CO2

concentration indicators, specifically end-tidal (PETCO2),

arterial (PaCO2), and internal jugular vein (PjvCO2) were

investigated and their corresponding cerebrovascular

reactivity were further studied [6]. The results revealed

that PaCO2 is overestimated by PETCO2 during hypercapnia

but not hypocapnia, thus underestimating CVMR. With

regards to PjvCO2, while the results indicate that reactivity

is higher, without further clarification as to the

mechanisms of CO2 flux across the brain, the actual

physiological significance of CVMR may be unclear. A

study on the effects of posture change on control of

ventilation [7] was conducted to examine the ventilatory

response to CO2 during supine and 75° head-up tilt (HUT)

350

Journal of Medical and Bioengineering Vol. 4, No. 5, October 2015

©2015 Engineering and Technology Publishingdoi: 10.12720/jomb.4.5.350-356

National Taiwan University Taipei, Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics, ,

in 11 healthy male subjects. The results indicated that

minute expiratory ventilation (V̇E) and tidal volume (VT)

increased during HUT while PETCO2 and transcutaneous

PCO2 decreased. The changes in PaCO2, alveolar ventilation

( V̇A ), and CBF velocity (CBFV) in the middle and

anterior cerebral arteries were recorded for 15 subjects

during HUT [8]. It was found that PaCO2 and PETCO2

decreased during HUT while increased. Also, CBFV

decreased throughout HUT even after decreases in PaCO2

has become smaller. Based on these results, it was

suggested that reductions in PaCO2 is not solely due to the

increased and other factors in addition to PaCO2 play a role

in the reduction of CBFV. Previous studies also depicted

that altered CBF may be an important contributor to

breathing instabilities during sleep [9], Meanwhile, he

indomethacin-induced reduction in the cerebrovascular

response to CO2 was associated with an increase in the

ventilatory response to CO2 and this observation raises

the possibility that disease states associated with an

attenuated cerebrovascular responsiveness to CO2 [10].

Through the analysis of the cardiovascular and

respiratory responses, the purpose of this study is to

understand the effects of nerve degeneration on the

human body focusing on the autonomic nervous system

(ANS) during hyperventilation and posture change for

ANS impaired patients. Specifically this study will be

taking a look at how the how cerebral autoregulation (CA)

and control of ventilation is affected in patients with

degenerated nerves such as Parkinson’s. This will be

accomplished by inducing changes in posture and CO2 in

the patients and studying how CA and ventilatory

parameters reacts to these changes compared to healthy

subjects. From the results of the experiment and analysis,

a better understanding of how the two auto-regulating

systems of a patient with an impaired ANS responds

when stressed will be gained.

II. METHODS

TABLE I. BASIC DATA OF SUBJECT GROUPS

Groups Subjects Age

Gender Number Total

Healthy-45- M 4

13 29.3 ± 7.4 F 9

Healthy-45+ M 7

9 56.5 ± 9.0 F 2

PD Patients M 7

13 58.9 ± 12.8 F 6

A. Subjects

The subjects for this study were recruited from the

database of patients from Cheng-Ching General Hospital

(CCGH), Taichung, Taiwan. The subjects were classified

into the groups of healthy elders over 45 years of age

(Healthy-45+), healthy youths under 45 years of age

(Healthy-45-), patients with Parkinson’s disease (PD).

The basic information of subjects is shown in Table I. All

healthy subjects have no history of cardiovascular,

respiratory, or neurological conditions. Parkinson’s

disease patients were evaluated based on the Unified

Parkinson’s Disease Rating Scale. All of the subjects in

this study have given their informed consent and the

study has passed inspection by the institutional review

board at CCGH and complies with human subject

protection regulations laid out by Taiwan Ministry of

Health and Welfare.

B. Experiment

The HR, ABP, CBFV, PETCO2, airflow, and were

recorded for each subject throughout the experiment.

Continuous ABP and HR were recorded using Finapres

(Model 2300, Ohmeda, Englewood, CO) on the right

hand middle finger of each subject. The height of the

finger is kept at equal height with the subject’s heart,

including during HUT. The Finapres device used in this

study is fully automated to adjust pressure accordingly

with the volume changes in the finger artery. However

because of the adjustment movement, servo components

were introduced into the recorded data. These servo

components are removed using special techniques

outlined in a previous study [11]. CBFV was measured

using a Transcranial Doppler Ultrasound (TCD, EME

TC2020, Nicolet Instruments, Warwick, UK) isolated at

5-MHz over the temporal window using an elastic

headband. Continuous PETCO2 and airflow signals were

recorded using a Capnography (Neoset, FS-01382,

SPEGAS Industries Ltd., Jerusalem, Israel). All signals

were sampled at 60 Hz and recorded simultaneously to

PC using LabVIEW® for offline analysis.

Subjects were examined on a motor-driven tilt-table

able to change the position of a patient from supine to 70°

head-up within 4 seconds. Before data acquisition began,

subjects first relaxed in the supine position for 10 minutes.

The subject’s ABP, CBFV, PETCO2, airflow, and heart rate

(HR) were all recorded continuously throughout the

protocol. First, the subject’s baseline data was recorded

for 5 minutes at supine rest. Then the subject underwent

voluntary hyperventilation in the supine position where

the subject breathed in for 5 seconds and out for 5

seconds. The deep breathing hyperventilation phase

lasted for about 1 minute or about 6 cycles after which

the subject is allowed to breathe normally. After 5 minute

of rest the subject is then tilted head-up by 75° for 10

minutes while breathing normally. At the end of the HUT,

the subject is then returned to the supine resting position.

The experiment protocol and procedure conducted in this

study are depicted in Fig. 1.

Figure 1. Experiment protocol.

351


©2015 Engineering and Technology Publishing

Figure 2. Note how the caption is centered in the column.

C. Signal Processing

Prior to the temporal data analysis, the acquired signals

from all subjects were processed with following steps, as

were concluded in Fig. 2.

Signals were recorded through Finapres, TCD, and

Neoset based on experiment protocol.

Acquired data were stored and servo components

were removed.

PETCO2 peak detection was based on finding the

max point between sections. These sections were

defined by intersects between a moving average

curve and the PETCO2 signal where the first

intersect was of a positive slope followed by one

with a negative slope.

PETCO2 peak interpolation was performed using

cubic Hermite spline at 3 samples per second.

Data points that exceeded the mean of 50 prior and

50 subsequent points by one standard deviation

were replaced with the mean value.

Mean PETCO2 during hyperventilation was

calculated by taking only the first 3 minutes of

hyperventilation.

Lowest PETCO2 section was found as the section of

data during the 3 minutes lower than Mean PETCO2.

Mean CBFV of the lowest Mean PETCO2 section

was determined by taking the mean of the CBFV

data corresponding to the section of lowest Mean

PETCO2 found in the previous step.

The percentage change in CBFV was calculated

using the Eq. (1) with respect to the baseline.

∆CBFV = (𝑥−𝑦

𝑦) × 100% . (1)

D. Signal Analysis

Analysis of the data was performed using the

LabVIEW® system design software. Before data analysis

can begin, the continuous raw data acquired must be first

organized and categorized into the respective groups and

states. The average values of MAP, systolic arterial

pressure (SAP), HR, CBFV, breathing rate (BR), and

PETCO2 will be calculated for each group under each state

(supine, hyperventilation, HUT). The mean changes in

MABP, HR, SBP, BR, and CBFV between subject

groups were examined in the time domain. Examining

when these changes occur and how long it takes before

physiological changes occur in response to stimulants, a

different view on the mechanisms of regulation was seen.

III. RESULTS

The results of the changes to the cardio-respiratory

parameters induced by the data acquisition protocol are

shown in Table II for the three different groups of

subjects included in the study. For the HEALTHY-45-

group, PETCO2 had a mean baseline of 30.88 (mmHg) at

rest, 13.20 (mmHg) during hyperventilation, and 28.24

(mmHg) during tilt-up. Mean systolic blood pressure

(MSBP) was 123.75, 125.41, and 133.93 (mmHg)

respectively. Mean arterial blood pressure (MABP) was

84.57, 84.05, and 96.95 mmHg respectively. Mean heart

rate (MHR) was 65.80, 68.43, and 71.94 (b/min)

respectively. Mean breathing rate (MBR) was 18.11,

38.82, 17.25 (breaths/min) respectively. Mean cerebral

blood flow velocity (MCBFV) was 49.67, 36.20, 45.50

(cm/sec) respectively. For the HEALTHY-45+ group,

PETCO2 had a mean baseline of 28.03 (mmHg) at rest, 9.81

(mmHg) during hyperventilation, and 25.03 (mmHg)

during tilt-up. The MSBP was 121.25, 125.41, and

130.39 (mmHg) respectively. The MABP was 88.45,

91.32, and 95.68 (mmHg) respectively. The MHR was

64.31, 73.49, and 68.20 (b/min) respectively. The MBR

was 16.61, 29.63, 17.44 breaths pre minute respectively.

The MCBFV was 39.00, 24.37, 38.68 (cm/sec)

respectively. For the Parkinson’s disease (PD) group,

PETCO2 had a mean baseline of 27.65 (mmHg) at rest,

13.12 (mmHg) during hyperventilation, and 25.22

(mmHg) during tilt-up. The MSBP was 122.41, 128.59,

and 124.11 (mmHg) respectively. The MABP was 85.92,

91.81, and 88.08 mmHg respectively. The MHR was

69.16, 73.49, and 68.20 (b/min) respectively. The MBR

was 16.61, 29.63, 17.44 (breaths/min) respectively. The

MCBFV was 39.00, 24.37, 38.68 (cm/sec) respectively.

TABLE II. CARDIO-RESPIRATORY PARAMETERS FOR TEST SUBJECTS

Supine (rest)

Subjects PETCO2 MSBP (mmHg) MABP MHR MBR MCBFV

352



(mmHg) (mmHg) (beat/min) (breath/min) (cm/s)

Healthy-45- 30.88±2.77† 123.75±11.44 84.57±8.97 65.80±8.56 18.11±2.58† 49.67±15.28†

Healthy-

45+ 28.03±3.55 121.25±8.22 88.45±8.88 64.31±9.30 16.14±2.26‡ 39.00±11.39

PD 27.65±4.56 122.41±21.24 85.92±15.1 69.16±12.63 17.34±3.92 36.95±12.22

Supine (hyperventilation)

Subjects PETCO2 (mmHg) MSBP (mmHg) MABP

(mmHg)

MHR

(beat/min)

MBR

(breath/min)

MCBFV

(cm/s)

Healthy-45- 13.20±3.69†‡ 125.41±13.29 84.05±8.97† 68.43±8.27 38.82±21.62‡ 36.20±13.77†‡

Healthy-

45+ 9.81±4.07‡ 125.41±13.33‡ 91.32±10.29 73.49±9.79‡ 29.63±4.40‡ 24.37±9.64‡

PD 13.12±5.71‡ 128.59±24.84 91.81±16.19‡ 73.37±15.2‡ 29.45±3.71‡ 28.29±10.07‡

Tilt up

Subjects PETCO2 (mmHg) MSBP (mmHg) MABP

(mmHg)

MHR

(beat/min)

MBR

(breath/min)

MCBFV

(cm/s)

Healthy-45- 28.24±3.29†‡ 133.93±16.56‡ 96.95±14.63‡ 71.94±9.57‡ 17.25±2.41 45.50±13.37‡

Healthy-

45+ 25.03±4.71‡ 130.39±19.17 95.68±10.94‡ 68.20±7.58‡ 17.44±3.15‡ 38.68±10.16

PD 25.22±5.66 124.11±24.52 88.08±17.86 76.96±13.30‡ 17.74±3.22 33.03±12.53 †Significant difference compared to Over 45 (P < 0.05) ‡Significant difference compared to baseline (rest) within group (P < 0.05)

Figure 3. Changes in parameters at different levels of PETCO2.

A. Cardiovascular and Respiratory Responses to CO2

In terms of changes in systemic cardio-vasculature,

there did not seem to be any significant changes for the

MABP of the HEALTHY-45+ group over the range of end-

tidal carbon dioxide levels obtained in this study of

approximately between 5~40 mmHg. This coincided with

the results from earlier study [12] in that below the level

of 40 mmHg there seemed to be little to no changes at all

for MABP. However, for the HEALTHY-45- group, there

seemed to be almost a difference of 20% between the

lowest and highest PETCO2 values. In Fig. 3, the

cardiovascular and respiratory responses to CO2,

including variations of MSBP, MABP, MHR, and MBR

(from top to bottom) were shown for three subject groups.

In each parameter, the spread of data was relatively wide

and shows no significant correlation between each

parameter and PETCO2.

B. Temporal Analysis for Cardiovascular and

Respiratory Parameters

Figure 4. Temporal responses of ΔPETCO2.

Figure 5. Temporal responses of ΔMSBP.

In this section, we show the temporal variation from

baseline data of each cardiovascular and respiratory

parameter, including PETCO2, MSBP, MABP, MHR, and

MBR, from Fig. 4 to Fig. 8, respectively. The percentage

353



change of each parameter was presented for rest,

hyperventilation, and tilt-up from left to right, and for the

HEALTHY-45-, HEALTHY-45

+, and PD from top to

bottom in each figure. For every individual group, mean

values of 5 seconds of data were displayed for analysis.

In Fig. 4, it clearly shows a drop in ΔPETCO2 levels to

below -60% for the HEALTHY-45+, below -50% for the

HEALTHY-45-, and to below -40% for the PD. During

tilt-up, PETCO2 levels initially dropped to below -20% for

all groups and slowly rose over time where it seemed to

level off at around -10% less than baseline.

Figure 6. Temporal responses of ΔMABP.

Figure 7. Temporal responses of ΔMHR.

Figure 8. Temporal responses of ΔMBR.

Figure 9. Temporal responses of ΔMCBFV.

Baseline changes for ΔMSBP, shown in Fig. 5,

fluctuated between 5% to -5% and drops sharply at the

beginning of hyperventilation to below -5% then rose

quickly as hyperventilation progressed. ΔMSBP then

reached peak value after approximately 100 seconds of

hyperventilation after which ΔMSBP began to drop back

down to baseline value with an oscillation effect for the

HEALTHY-45+. For the PD, the ΔMSBP continuously rose

throughout the hyperventilation period and continued to

do so even after hyperventilation has stopped and peaked

out at around 10%. During tilt-up, the healthy control

group showed an increase of around 10% in ΔMSBP and

while PD group showed the same change of around 10%,

it dropped first by approximate 10% before rising back up

to just above baseline. ΔMABP changes, shown in Fig. 6,

followed a similar pattern to that of ΔMSBP where there

was a slight oscillation around -5% to 5% during rest for

all groups. During hyperventilation, ΔMABP increased

quickly to approximately 10% before dropping back

down to resting levels in the HEALTHY-45+. For the

HEALTHY-45-, ΔMABP remained relatively stable until

the end of hyperventilation after which began to oscillate

again. In the PD, however, MABP rose throughout

hyperventilation and continued to increase after

hyperventilation has ended to close to 20%. During tilt,

both control groups had MABP rising above 10% while

the PD also had a small rise to above baseline values.

As can be seen in Fig. 7, ΔMHR showed no significant

fluctuations during rest for all the groups. However,

during hyperventilation, ΔMHR increased to 20% for the

HEALTHY-45+, 10% for both the HEALTHY-45

+ and PD.

ΔMHR for all four groups dropped back down to baseline

after hyperventilation had ended. All groups also showed

an increase during tilt-up to just fewer than 10% for the

HEALTHY-45+ and greater than 10% for the PD group,

while the HEALTHY-45- ΔMHR oscillated around 10%.

Fig. 8 shows the ΔMBR over time that, due to experiment

protocol, the breathing rate during hyperventilation was

increased by 100%. After hyperventilation had ended, the

breathing rate returned back to baseline values. During

head up tilt, although hard to see due to the scale, the

ΔMBR rose slightly to around 7% for the HEALTHY-45+

and around 4% for the PD group while values for the

HEALTHY-45- remained close to the baseline.

354



C. Temporal Analysis for Cerebral Blood Flow

In Fig. 9, the variation of MCBFV was depicted for

temporal analysis of PD in comparison with healthy

subjects. At rest, the HEALTHY-45+ showed continuous

changes within the range from 10% to -10% while the

HEALTHY-45- and PD showed changes but to a lesser

degree. During hyperventilation, all groups displayed a

rapid drop in ΔMCBFV, by -40% for the healthy groups,

and by -20%~-30% for the PD. After hyperventilation

had ended at approximately time 175 (sec.), ΔMCBFV of

all groups returned to baseline values. However, the PD-

showed a faster rise in ΔMCBFV but overshot the

baseline to 20% before lowering back down to baseline

values. The healthy groups showed a gradual increase

back to baseline values. During tilt all groups showed an

initial drop with the ΔMCBFV of the HEALTHY-45+

slowly climbing back up to baseline values while the

HEALTHY-45- continued dropping throughout tilt-up. For

the PD, ΔMCBFV remained slightly under baseline for

the duration of the tilt-up phase.

IV. DISCUSSION AND CONCLUSION

Comparison of MABP between the results of this study

and earlier finding [12], it seemed to be consistent

between the two for levels below 40 mmHg. Both studies

showed that with lower levels of PETCO2, MABP did not

change relative to the baseline. Not only was this true for

healthy subjects, but it was also true for subjects with

Parkinson’s disease. This suggested that vessel reaction

to changes in PETCO2 was the same without any

impairment even in subjects with Parkinson’s disease.

Comparing the breathing parameter of MBR between

healthy elderly group and the Parkinson’s group, there

also were not any differences regarding the range of

changes at the different levels of PETCO2.

In terms of PETCO2, there seemed to be no clear

difference in the rise and fall over time between the

healthy groups and the PD. However, the results showed

that the range of the change during hypocapnia was

greater in the healthy youth group than in the PD-group.

This suggested that the regulation of PETCO2 might have

been impaired leading to a greater reactivity to PETCO2 and

thus a more limited range. During head up tilt, similar to

other experimental results [13], there was a decrease in

PETCO2 from baseline of around 5% to 10% and did not

return to baseline values until tilt-up has ended. This

decrease might be explained by the approximately 1 extra

breath per minute increase in breathing rate during tilt-up,

but without knowing if ventilation has increased, there is

no way of making certain if the fall in PETCO2 can be for

sure attributed by an increase in ventilation.

Regarding systemic hemodynamic changes over time,

intracranial pressure appeared to have been decreased due

to hyperventilation that in turn caused MCBFV to fall,

and consequently the body compensated by increasing

blood pressure and heart rate. Current results for the

healthy elders coincided with other finding [4]. However,

for the healthy youth group, blood pressure remained

relatively unchanged and only compensated for the

changes in MCBFV by increasing HR. For the PD group,

it would seem that ABP and HR both attempted to

compensate for the drop in CBFV during hyperventilation,

but overcompensated and ABP continued to rise after

hyperventilation ended. The overcompensation caused

CBFV to overshoot before returning to the baseline. This

suggested that PD patients might have some form of

regulation impairment which was causing ABP to

continue to rise even though HR had already stopped

rising and led to overcompensation of CBFV past the

baseline. This impairment was further supported by the

results from tilt-up testing. The healthy groups showed

the normal response where the blood pressure and heart

rate increased to overcome the drop in CBFV caused by

the cerebral pressure drop due to the change in posture.

However for the PD group, even though heart rate

increased as it would in a normal response, blood

pressure dropped after tilt-up but only increased until

baseline where it remained throughout the duration of tilt-

up. This caused CBFV to remain below baseline which

once again suggested the impairment of CA.

ACKNOWLEDGMENT

This study was supported by the Ministry of Science

and Technology (MOST 103-2221-E-035 -004), Taiwan.

REFERENCES

[1] M. A. Pfeifer, C. R. Weinberg, D. Cook, J. D. Best, A. Reenan,

and J. B. Halter, “Differential changes of autonomic nervous

system function with age in man,” The American J. of Medicine, vol. 75, pp. 249-258, 1983.

[2] P. N. Ainslie and J. Duffin, “Integration of cerebrovascular CO2

reactivity and chemoreflex control of breathing: Mechanisms of regulation, measurement, and interpretation,” American J. of

Physiology-Regulatory, Integrative and Comparative Physiology,

vol. 296, no. 5, pp. R1473-R1495, May 2009. [3] K. Ide, M. Eliasziw, and M. J. Poulin, “Relationship between

middle cerebral artery blood velocity and end-tidal PCO2 in the

hypocapnic-hypercapnic range in humans,” J. of Applied Physiology, vol. 95, pp. 129-137, 2003.

[4] J. A. H. R. Claassen, R. Zhang, Q. Fu, S. Witkowski, and B. D.

Levine, “Transcranial doppler estimation of cerebral blood flow and cerebrovascular conductance during modified rebreathing,”

Journal of Applied Physiolog, vol. 102, pp. 870-877, 2007.

[5] A. Battisti-Charbonney, J. Fisher, and J. Duffin, “The

cerebrovascular response to carbon dioxide in humans,” The J. of

Physiology, vol. 589, pp. 3039-3048, 2011.

[6] K. Peebles, L. Celi, K. McGrattan, C. Murrell, K. Thomas, and P. N. Ainslie, “Human cerebrovascular and ventilatory CO2

reactivity to end-tidal, arterial and internal jugular vein PCO2,”

The J. of Physiology, vol. 584, pp. 347-357, 2007. [7] H. Yoshizaki, A. Yoshida, F. Hayashi, and Y. Fukuda, “Effect of

posture change on control of ventilation,” Japanese J. of

Physiology, vol. 48, pp. 267-273, 1998. [8] J. M. Serrador, R. L. Hughson, J. M. Kowalchuk, R. L. Bondar,

and A. W. Gelb, “Cerebral blood flow during orthostasis: Role of

arterial CO2,” American J. of Physiology-Regulatory, Intergrative and Comparative Physiology, vol. 290, pp. R1087-R1093, 2006.

[9] A. Xie, J. B. Skatrud, R. Khayat, J. A. Dempsey, B. Morgan, and

D. Russell, “Cerebrovascular response to carbon dioxide in patients with congestive heart failure,” American J. of Respiraion

and Critical Care Medicine, vol. 172, pp. 371-378, 2005. [10] A. Xie, J. B. Skatrud, B. Morgan, B. Chenuel, R. Khayat, K.

Reichmuth, J. Lin, and J. A. Dempsey, “Influence of

cerebrovascular function on the hypercapnic ventilatory response in healthy humans,” The J. of Physiology, vol. 577, pp. 319-329,

2006.

355



[11] C. C. Chiu and S. J. Yeh, “Assessment of cerebral autoregulation using time-domain cross-correlation analysis,” Computers in

Biology and Medicine, vol. 32, pp. 471-480, 2001,

[12] C. K. Willie, D. B. Macleod, A. D. Shaw, K. J. Smith, Y. C. Tzeng, et al., “Regional brain blood flow in man during acute

changes in arterial blood gases,” The J. of Physiology, vol. 590, pp.

3261-3275, 2012. [13] R. V. Immink, J. Truijen, N. H. Secher, and J. J. Van Lieshout,

“Transient influence of end-tidal carbon dioxide tension on the

postural restraint in cerebral perfusion,” J. of Applied Physiology, vol. 107, pp. 816-823, 2009.

Shyan-Lung Lin was born in Taiwan on January 22, 1963. After graduated from E.E.

Department of Ming Chi Institute of

Technology, Taiwan, and finished his Navy ROTC service in 1983 and 1985, respectively,

he earned his M.S. in Electrical and Electronic

Engineering at North Dakota State University, Fargo, USA in 1988 and received his Ph.D. in

Electrical Engineering and Computer Science

at Northwestern University, Evanston, Illinois, USA in 1992. She joined Department of Automatic Control Engineering,

Feng Chia University, Taichung, Taiwan in 1992 as an Associate

Professor. Since 2014, Dr. Lin is also a joint Associate Professor in Department of Information Communication at MingDao University,

Changhua, Taiwan. His research specialty includes respiratory control,

biomedical control and simulation, numerical and parallel computations. Prof. Lin has published over 150 papers in referred journal and

conference and participated over 40 grant-projects from National

Science Council, Taiwan, during the past 20 years.

356



journal of medical and bioengineering vol. 4, no. 5

Documents